Scaling the iHMM: Parallelization versus Hadoop

Proceedings - 10th IEEE International Conference on Computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, ScalCom-2010

Volumn , Issue , 2010, Pages 1235-1240

  Bratières, Sébastien ^a   Van Gael, Jurgen ^a   Vlachos, Andreas ^a   Ghahramani, Zoubin ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DISTRIBUTED IMPLEMENTATION; DYNAMIC PROGRAMS; GIBBS SAMPLING; MACHINE LEARNING ALGORITHMS; PARALLELIZATIONS; PART-OF-SPEECH TAGS; PROBABILISTIC MODELS; RUNTIME PERFORMANCE;

EMBEDDED SYSTEMS; INFORMATION TECHNOLOGY; LEARNING ALGORITHMS;

EMBEDDED SOFTWARE;

EID: 78249272651     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIT.2010.223     Document Type: Conference Paper

References (11)

1. M. J. Beal, Z. Ghahramani, and C. E. Rasmussen, "The Infinite Hidden Markov Model, " Advances in Neural Information Processing Systems, vol. 14, pp. 577 - 584, 2002.
2. G. Bradski, C.-T. Chu, A. Ng, K. Olukotun, S. K. Kim, Y.-A. Lin, and Y. Yu, "Map-reduce for machine learning on multicore, " in NIPS, 2006.
3. L. E. Baum, T. Petrie, G. Soules, and N. Weiss, "A maximization technique occurring in the statistical analysis of probabilistic functions of markov chains, " The Annals of Mathematical Statistics, vol. 41, no. 1, pp. 164-171, 1970.
4. Y. W. Teh, M. I. Jordan, M. J. Beal, and D. M. Blei, "Hierarchical Dirichlet processes, " Journal of the American Statistical Association, vol. 101, no. 476, pp. 1566-1581, 2006.
5. J. Van Gael, Y. Saatci, Y. W. Teh, and Z. Ghahramani, "Beam Sampling for the Infinite Hidden Markov Model, " in Proceedings of the 25th International Conference on Machine learning, Helsinki, 2008.
6. C. D. Manning and H. Schuetze, Foundations of Statistical Natural Language Processing, 1st ed. The MIT Press, Jun. 1999.
7. M. Johnson, "Why Doesn't EM Find Good HMM POSTaggers?" in Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2007, pp. 296- 305.
8. S. Goldwater and T. Griffiths, "A fully Bayesian approach to unsupervised part-of-speech tagging, " in Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Prague, Czech Republic: Association for Computational Linguistics, June 2007, pp. 744-751.
9. J. Van Gael, A. Vlachos, and Z. Ghahramani, "The infinite HMM for unsupervised PoS tagging, " in Proceedings of 2009 Conference on Empirical Methods in Natural Language Processing, Singapore, 2009, pp. 678-687.
10. M. Meilà, "Comparing clusterings-an information based distance, " Journal of Multivariate Analysis, vol. 98, no. 5, pp. 873-895, 2007.
11. B. C. M. Fung, K. Wang, and M. Ester, "Hierarchical document clustering using frequent itemsets, " in Proceedings of SIAM International Conference on Data Mining, 2003, pp. 59-70.